class_docstr: A class for generating signals from streamlines in an efficient and speedy
  manner.
code: def calc_signal(self, xyz):
      idx = self.sphere.find_closest(xyz)
      if idx not in self._calculated:
          bvecs = self.gtab.bvecs[~self.gtab.b0s_mask]
          bvals = self.gtab.bvals[~self.gtab.b0s_mask]
          tensor = grad_tensor(self.sphere.vertices[idx], self.evals)
          ADC = np.diag(np.linalg.multi_dot([bvecs, tensor, bvecs.T]))
          sig = np.exp(-bvals * ADC)
          sig = sig - np.mean(sig)
          self.signal[idx] = sig
          self._calculated.append(idx)
  
      return self.signal[idx]
  
imports: import numpy
  import scipy.sparse
  import scipy.linalg
  from dipy.reconst.base import ReconstModel, ReconstFit
  from dipy.tracking.utils import unique_rows
  from dipy.tracking.streamline import transform_streamlines
  from dipy.tracking.vox2track import _voxel2streamline
  import dipy.data
  import dipy.core.optimize
label_desc: Use image node_id 2 for calling the LifeSignalMaker obj's underlying member method code with example usage: obj.calc_signal(xyz) and returns: self